In [1]:
from herschelhelp_internal import git_version
print("This notebook was run with herschelhelp_internal version: \n{}".format(git_version()))
In [2]:
%matplotlib inline
#%config InlineBackend.figure_format = 'svg'
import matplotlib.pyplot as plt
plt.rc('figure', figsize=(10, 6))
plt.style.use('ggplot')
import locale
locale.setlocale(locale.LC_ALL, 'en_GB')
import os
import time
import itertools
from astropy.coordinates import SkyCoord
from astropy.table import Table
from astropy import units as u
from astropy import visualization as vis
import numpy as np
from matplotlib_venn import venn3, venn2
from herschelhelp_internal.masterlist import (nb_compare_mags, nb_ccplots, nb_histograms, find_last_ml_suffix,
quick_checks)
In [3]:
OUT_DIR = os.environ.get('OUT_DIR', "./data")
SUFFIX = find_last_ml_suffix()
#SUFFIX = "20171016"
master_catalogue_filename = "master_catalogue_ssdf_{}.fits".format(SUFFIX)
master_catalogue = Table.read("{}/{}".format(OUT_DIR, master_catalogue_filename))
print("Diagnostics done using: {}".format(master_catalogue_filename))
0 - Quick checks¶
In [4]:
quick_checks(master_catalogue).show_in_notebook()
Out[4]:
I - Summary of wavelength domains¶
In [5]:
flag_obs = master_catalogue['flag_optnir_obs']
flag_det = master_catalogue['flag_optnir_det']
In [6]:
venn3(
[
np.sum(flag_obs == 4),
np.sum(flag_obs == 2),
np.sum(flag_obs == 6),
np.sum(flag_obs == 1),
np.sum(flag_obs == 5),
np.sum(flag_obs == 3),
np.sum(flag_obs == 7)
],
set_labels=('Optical', 'near-IR', 'mid-IR'),
subset_label_formatter=lambda x: "{}%".format(int(100*x/len(flag_obs)))
)
plt.title("Wavelength domain observations");
In [7]:
venn3(
[
np.sum(flag_det[flag_obs == 7] == 4),
np.sum(flag_det[flag_obs == 7] == 2),
np.sum(flag_det[flag_obs == 7] == 6),
np.sum(flag_det[flag_obs == 7] == 1),
np.sum(flag_det[flag_obs == 7] == 5),
np.sum(flag_det[flag_obs == 7] == 3),
np.sum(flag_det[flag_obs == 7] == 7)
],
set_labels=('Optical', 'near-IR', 'mid-IR'),
subset_label_formatter=lambda x: "{}%".format(int(100*x/np.sum(flag_det != 0)))
)
plt.title("Detection of the {} sources detected\n in any wavelength domains "
"(among {} sources)".format(
locale.format('%d', np.sum(flag_det != 0), grouping=True),
locale.format('%d', len(flag_det), grouping=True)));
II - Comparing magnitudes in similar filters¶
The master list if composed of several catalogues containing magnitudes in similar filters on different instruments. We are comparing the magnitudes in these corresponding filters.
In [8]:
g_bands = ["DECam g"]
r_bands = ["DECam r"]
i_bands = ["DECam i"]
z_bands = ["DECam z"]
y_bands = ["DECam y"]
j_bands = [ "VISTA j"]
h_bands = [ "VISTA h"]
k_bands = [ "VISTA k"]
irac_bands = ["IRAC I1", "IRAC I2"]
II.a - Comparing depths¶
We compare the histograms of the total aperture magnitudes of similar bands.
In [9]:
for bands in [g_bands + r_bands + i_bands + z_bands + y_bands, j_bands + h_bands + k_bands, irac_bands]:
colnames = ["m_{}".format(band.replace(" ", "_").lower()) for band in bands]
nb_histograms(master_catalogue, colnames, bands)
II.b - Comparing magnitudes¶
There are no similar bands from different instruments.
In [10]:
# for band_of_a_kind in [j_bands, h_bands, k_bands]:
# for band1, band2 in itertools.combinations(band_of_a_kind, 2):
#
# basecol1, basecol2 = band1.replace(" ", "_").lower(), band2.replace(" ", "_").lower()
#
# col1, col2 = "m_ap_{}".format(basecol1), "m_ap_{}".format(basecol2)
# nb_compare_mags(master_catalogue[col1], master_catalogue[col2],
# labels=("{} (aperture)".format(band1), "{} (aperture)".format(band2)))
#
# col1, col2 = "m_{}".format(basecol1), "m_{}".format(basecol2)
# nb_compare_mags(master_catalogue[col1], master_catalogue[col2],
# labels=("{} (total)".format(band1), "{} (total)".format(band2)))
III - Comparing magnitudes to reference bands¶
Cross-match the master list to SDSS.
In [11]:
master_catalogue_coords = SkyCoord(master_catalogue['ra'], master_catalogue['dec'])
III.b - Comparing J and K bands to 2MASS¶
The catalogue is cross-matched to 2MASS-PSC withing 0.2 arcsecond. We compare the UKIDSS total J and K magnitudes to those from 2MASS.
The 2MASS magnitudes are “Vega-like” and we have to convert them to AB magnitudes using the zero points provided on this page:
| Band | Fν - 0 mag (Jy) |
|---|---|
| J | 1594 |
| H | 1024 |
| Ks | 666.7 |
In [12]:
# The AB zero point is 3631 Jy
j_2mass_to_ab = 2.5 * np.log10(3631/1595)
k_2mass_to_ab = 2.5 * np.log10(3631/666.7)
In [13]:
twomass = Table.read("../../dmu0/dmu0_2MASS-point-sources/data/2MASS-PSC_SSDF.fits")
twomass_coords = SkyCoord(twomass['raj2000'], twomass['dej2000'])
idx, d2d, _ = twomass_coords.match_to_catalog_sky(master_catalogue_coords)
mask = (d2d < 0.2 * u.arcsec)
twomass = twomass[mask]
ml_twomass_idx = idx[mask]
In [14]:
nb_compare_mags(twomass['jmag'] + j_2mass_to_ab, master_catalogue['m_vista_j'][ml_twomass_idx],
labels=("2MASS J", "VISTA J (total)"))
In [15]:
nb_compare_mags(twomass['kmag'] + k_2mass_to_ab, master_catalogue['m_vista_k'][ml_twomass_idx],
labels=("2MASS Ks", "VISTA Ks (total)"))
IV - Comparing aperture magnitudes to total ones.¶
In [16]:
nb_ccplots(
master_catalogue['m_vista_j'],
master_catalogue['m_ap_vista_j'] - master_catalogue['m_vista_j'],
"j total magnitude (VISTA)", "j aperture mag - total mag (VISTA)",
master_catalogue["stellarity"],
invert_x=True
)
In [17]:
nb_ccplots(
master_catalogue['m_irac_i1'],
master_catalogue['m_ap_irac_i1'] - master_catalogue['m_irac_i1'],
"irac_i1 total magnitude (SSDF)", "irac_i1 aperture mag - total mag (SSDF)",
master_catalogue["stellarity"],
invert_x=True
)
V - Color-color and magnitude-color plots¶
In [18]:
nb_ccplots(
master_catalogue['m_vista_j'] - master_catalogue['m_vista_h'],
master_catalogue['m_vista_k'] - master_catalogue['m_irac_i1'],
"J - H (VISTA)", "Ks - irac_i1 (VISTA, SSDF)",
master_catalogue["stellarity"]
)
In [19]:
nb_ccplots(
master_catalogue['m_irac_i1'] - master_catalogue['m_irac_i2'],
master_catalogue['m_vista_j'] - master_catalogue['m_vista_k'],
"irac_i1 - irac_i1", "VISTA J - VISTA Ks",
master_catalogue["stellarity"]
)
